Summary

Row

Total Test Conducted

9,666

Positive

49

active

37

recovered

12 ( 24.5 % )

death

0 ( 0 % )

Row

Total Positive Cases in Nepal

Row

RT-PCR Tests Conducted

Data

---
title: "COVID-19 Nepal"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    social: menu
    source_code: embed
    vertical_layout: fill

knit: (function(input_file, encoding) {
  out_dir <- 'html';
  rmarkdown::render(input_file,
 encoding=encoding,
 output_file=file.path(dirname(input_file), out_dir, 'dashboard.html'))})    
---

```{r setup, include=FALSE}
### DEFINE LIBRARIES ---
library("flexdashboard")
library("ggplot2")
library("plotly")

# DATA CURATED FROM DATA RELEASED (UPDATED DAILY) FROM
# GOVT. OF NEPAL, MINISTRY OF HEALTH AND POPULATION
# HEALTH SECTOR RESPONSE TO CORONAVIRUS DISEASE (COVID-19)
# URL: https://drive.google.com/drive/folders/1QhLMbT76t6Zu1sFy5qlB5aoDbHVAcnHx

### DEFINE FILE ---
dir.data <- file.path("data")
file.dat <- file.path(dir.data, "data_total.tsv")

#------------------ Parameters ------------------
# Set colors
# https://www.w3.org/TR/css-color-3/#svg-color
test_color <- "#4292c6"
confirmed_color <- "#b15928"
active_color <- "#ff7f00"
recovered_color <- "#33a02c"
death_color <- "#e31a1c"

### LOAD DATA ---
dat <- read.delim(file.dat, header=TRUE, stringsAsFactors=FALSE)
dat$date <- as.Date(dat$date, format = "%m/%d/%y")

### FUNCTION: num_changes() ---
num_changes <- function(x){
  y <- numeric()
  y[1] <- x[1]
  
  for(i in 2:length(x)){
    y[i] <- x[i] - x[i-1]           
  }
  
  return(y)
}  

### CALCULATE ACTIVE INFECTION, NEW TESTS, NEW POITIVES, NEW DEATH, NEW RECOVERED ---
dat$active_case <- dat$total_positive - dat$total_recovered
dat$new_tested <- num_changes(dat$total_test)
dat$new_positive <- num_changes(dat$total_positive)	
dat$new_death <- num_changes(dat$total_death)	
dat$new_recovered <- num_changes(dat$total_recovered)

### LATEST INFO ---
total_test <- dat$total_test[nrow(dat)]
total_positive <- dat$total_positive[nrow(dat)]
active_case <- dat$active_case[nrow(dat)]
total_recovered <- dat$total_recovered[nrow(dat)]
total_death <- dat$total_death[nrow(dat)]
rate_recovry <- round((total_recovered/total_positive) * 100,1)
rate_death <- round((total_death/total_positive) * 100, 1)
```


Summary
=======================================================================
Row
-----------------------------------------------------------------------

### Total Test Conducted {.value-box}

```{r}
valueBox(value = paste(format(total_test, big.mark = ","), "", sep = " "), 
         caption = "Total Test Conducted", 
         icon = "fas fa-vial", 
         color = test_color)
```

### Positive {.value-box}

```{r}
valueBox(value = paste(format(total_positive, big.mark = ","), "", sep = " "), 
         caption = "Positive Cases", 
         icon = "fas fa-user-md", 
         color = confirmed_color)
```


### active {.value-box}

```{r}
valueBox(value = paste(format(active_case, big.mark = ","), "", sep = " "), 
         caption = "Active Cases", 
         icon = "fas fa-ambulance", 
         color = active_color)
```

### recovered {.value-box}

```{r}
valueBox(value = paste(format(total_recovered, big.mark = ","), "   (", format(paste(rate_recovry, "%", sep=" "), big.mark = ","), " )", "", sep = " "),  
         caption = "Recovered Cases", icon = "fas fa-heartbeat", 
         color = recovered_color)
```

### death {.value-box}

```{r}
valueBox(value = paste(format(total_death, big.mark = ","), "   (", format(paste(rate_death, "%", sep=" "), big.mark = ","), " )", "", sep = "  "), 
         caption = "Death Cases", 
         icon = "fas fa-bolt", 
         color = death_color)
```


Row
-----------------------------------------------------------------------

### Total Positive Cases in Nepal

```{r}
p1 <- ggplot(dat, aes(x=date, y=total_positive)) +
      geom_point(color=confirmed_color, alpha=1, size=2) +
      geom_line(color=confirmed_color, alpha=1, size=1)+
      theme(
        axis.text.x = element_text(size = 15, color="#000000"),
        axis.text.y = element_text(size = 15, color="#000000"),
        axis.title = element_text(size = 15, color="#000000"),
        plot.title = element_text(size = 15, color="#000000", hjust=0.5),
        panel.grid.major.y = element_line(size=0.5, color="#BDBDBD"),
        panel.grid.minor.y = element_line(size=0.25, color="#BDBDBD"),
        panel.grid.major.x = element_blank(),
        panel.grid.minor.x = element_blank(),
        axis.ticks = element_line(size=0.4, color="#000000"), 
        strip.text = element_text(size=10, color="#000000"),
        strip.background = element_rect(fill="#FFFFFF", color="#FFFFFF"),
        panel.background = element_rect(fill="#FFFFFF", color="#FFFFFF"),
        axis.line.x = element_line(size = 1.5, color="#000000"),
        axis.line.y = element_blank(),
        legend.text = element_text(size = 10, color="#000000"),
        legend.title = element_blank(),
        legend.key.size = unit(0.5, "cm"),
        legend.position = "none") +
      ylab("Total Positive Cases") +
      xlab("Date") + 
      ggtitle("") 

plotly::ggplotly(p1)
```

Row {data-width=400}
-----------------------------------------------------------------------


### RT-PCR Tests Conducted
    
```{r}
p2 <- ggplot(dat, aes(x=date, y=total_test)) +
      geom_point(color=test_color, alpha=1, size=2) +
      geom_line(color=test_color, alpha=1, size=1)+
      theme(
        axis.text.x = element_text(size = 15, color="#000000"),
        axis.text.y = element_text(size = 15, color="#000000"),
        axis.title = element_text(size = 15, color="#000000"),
        plot.title = element_text(size = 15, color="#000000", hjust=0.5),
        panel.grid.major.y = element_line(size=0.5, color="#BDBDBD"),
        panel.grid.minor.y = element_line(size=0.25, color="#BDBDBD"),
        panel.grid.major.x = element_blank(),
        panel.grid.minor.x = element_blank(),
        axis.ticks = element_line(size=0.4, color="#000000"), 
        strip.text = element_text(size=10, color="#000000"),
        strip.background = element_rect(fill="#FFFFFF", color="#FFFFFF"),
        panel.background = element_rect(fill="#FFFFFF", color="#FFFFFF"),
        axis.line.x = element_line(size = 1.5, color="#000000"),
        axis.line.y = element_blank(),
        legend.text = element_text(size = 10, color="#000000"),
        legend.title = element_blank(),
        legend.key.size = unit(0.5, "cm"),
        legend.position = "none") +
      ylab("Total RT-PCR Test Conducted") +
      xlab("Date") + 
      ggtitle("") 

plotly::ggplotly(p2) %>% layout(hoverlabel=list(bgcolor="#FFFFFF"))

```


### Data
    
```{r}
dtbl <- dat %>%
          dplyr::select(Date=date, 
                        'Total Test'=total_test, 
                        'Total Positive'=total_positive,
                        'Active Cases'=active_case,
                        'Total Recovered'=total_recovered,
                        'Total Death'=total_death)

dtbl$Date <- as.Date(dtbl$Date, format = '%Y/%m/%d')

dtbl <- dtbl[order(dtbl$Date, decreasing = TRUE),]

dtbl %>%  
  DT::datatable(rownames = FALSE,
            options = list(searchHighlight = TRUE, 
                           pageLength = 20))
```